旨在探索数据挖掘和神经网络技术在电力工程造价的实际应用,利用数据挖掘和神经网络技术创建电力工程造价审计的理论模型,在数据挖掘技术的作用下,完成数据预处理以及属性优选的相关工作,继而剖离出数据挖掘技术的模糊规则,并通过神经网络技术重构电力工程造价的预测方法。结论表明数据挖掘和神经网络技术可提高电力工程造价预测与审查的准确性。 The purpose of this paper is to explore the practical application of data mining and neural network technology in the cost of power engineering, to establish the theoretical model of power project cost audit by using data mining and neural network technology, and to complete the data preprocessing and attribute optimization by the data mining technology Work, and then cut out the fuzzy rules of data mining technology, and through neural network technology to reconstruct the forecast method of electricity project cost. The conclusion shows that data mining and neural network technology can improve the accuracy of power project cost forecasting and examination.